Electronic device and method for providing personalized biometric information based on biometric signal using same

ABSTRACT

An electronic device for providing biometric information is provided. The electronic device includes a sensor module, a memory, and a processor electrically connected to the sensor module and the memory. The processor obtains a biometric signal from the sensor module at a predetermined time interval, determines whether a user is in a first state on the basis of the obtained biometric signal, in case the user is in a first state, obtains a representative value for a respective of the at least one biometric signal, defines the obtained representative value for the respective of the at least one biometric signal as a candidate reference value for a corresponding biometric signal, determines a candidate reference value satisfying a predetermined condition as a first reference value for the corresponding biometric signal, and updates a second reference value previously configured for the corresponding biometric signal on the basis of the first reference value.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application is a continuation application of prior application Ser.No. 16/419,678, filed on May 22, 2019, which application is based on andclaims priority under 35 U.S.C. § 119(a) of a Korean patent applicationnumber 10-2018-0076439, filed on Jul. 2, 2018, in the KoreanIntellectual Property Office, the disclosure of which is incorporated byreference herein in its entirety.

BACKGROUND 1. Field

Various embodiments of the disclosure relate to an electronic device anda method for providing personalized biometric information based on abiometric signal.

2. Description of Related Art

In general, electronic devices have various kinds of sensors. Theelectronic devices may monitor user's behavior in real time usingvarious kinds of sensors provided therein. The electronic devices mayestimate biometric information (e.g., heart rate information, bloodpressure information, stress information, etc.) related to the user onthe basis of biometric signals obtained through monitoring of varioussensors, and may provide the estimated biometric information to theuser.

The above information is presented as background information only toassist with an understanding of the disclosure. No determination hasbeen made, and no assertion is made, as to whether any of the abovemight be applicable as prior art with regard to the disclosure.

SUMMARY

However, since a generalized model is used for estimating the biometricinformation related to the user despite the factors causing changes inthe body characteristics and biometric signals are different betweenusers, accurate biometric information (e.g., stress intensity) may notbe provided to the user.

Aspects of the disclosure are to address at least the above-mentionedproblems and/or disadvantages and to provide at least the advantagesdescribed below. Accordingly, an aspect of the disclosure is to providean electronic device that detects changes in the biometric signals(e.g., heart rate, blood pressure, skin temperature, skin resistance,etc.) obtained from sensors, and may store only the biometric signals inthe state in which no change is detected. The electronic device maydetermine personalized biometric information for the user on the basisof the stored biometric signals, and provide the user with informationon the biometric state on the basis of the determined biometricinformation.

Additional aspects will be set forth in part in the description whichfollows and, in part, will be apparent from the description, or may belearned by practice of the presented embodiments.

In accordance with an aspect of the disclosure, an electronic device isprovided. The electronic device includes a sensor module, a memory, andat least one processor electrically connected to the sensor module andthe memory, wherein the processor is configured to obtain at least onebiometric signal from the sensor module at a predetermined timeinterval, determine whether a user is in a first state on the basis ofthe obtained at least one biometric signal, in case the user is in thefirst state, obtain a representative value for a respective of the atleast one biometric signal, define the obtained representative value forthe respective of the at least one biometric signal as a candidatereference value for a corresponding biometric signal, determine acandidate reference value satisfying a predetermined condition as afirst reference value for the corresponding biometric signal, and updatea second reference value previously configured for the correspondingbiometric signal on the basis of the first reference value.

In accordance with another aspect of the disclosure, a method ofproviding personalized biometric information based on a biometric signalis provided. The method includes obtaining at least one biometricsignals from a sensor module at a predetermined time interval,determining whether a user is in a first state on the basis of theobtained at least one biometric signal, in case the user is in the firststate, obtaining a representative value for a respective of the at leastone biometric signal, defining the obtained representative value for therespective of the at least one biometric signal as a candidate referencevalue for a corresponding biometric signal, determining a candidatereference value satisfying a predetermined condition as a firstreference value for the corresponding biometric signal, and updating asecond reference value previously configured for the correspondingbiometric signal on the basis of the first reference value.

An electronic device according to various embodiments is able todetermine a personalized reference value for a biometric signal on thebasis of a biometric signal in the state in which no change in thebiometric signal obtained from the sensors is detected. The electronicdevice is able to provide the user with accurate biometric information(e.g., stress intensity) by comparing a personalized reference value fora biometric signal with biometric signal values obtained from thesensors.

Other aspects, advantages, and salient features of the disclosure willbecome apparent to those skilled in the art from the following detaileddescription, which, taken in conjunction with the annexed drawings,discloses various embodiments of the disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects, features, and advantages of certainembodiments of the disclosure will be more apparent from the followingdescription taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a block diagram of an electronic device that providespersonalized biometric information based on a biometric signal in anetwork environment according to various embodiments of the disclosure;

FIG. 2 is a block diagram illustrating an electronic device thatprovides personalized biometric information based on a biometric signalaccording to various embodiments of the disclosure;

FIG. 3 is a flowchart explaining a method for providing personalizedbiometric information based on a biometric signal according to variousembodiments of the disclosure;

FIG. 4 is a flowchart explaining a method for determining a referencevalue for providing personalized biometric information based on abiometric signal according to various embodiments of the disclosure;

FIG. 5 is a flowchart explaining a method for determining a referencevalue for providing personalized biometric information based on abiometric signal according to various embodiments of the disclosure; and

FIG. 6 is a flowchart explaining a method for providing personalizedbiometric information based on a biometric signal according to variousembodiments of the disclosure.

Throughout the drawings, like reference numerals will be understood torefer to like parts, components, and structures.

DETAILED DESCRIPTION

The following description with reference to the accompanying drawings isprovided to assist in a comprehensive understanding of variousembodiments of the disclosure as defined by the claims and theirequivalents. It includes various specific details to assist in thatunderstanding but these are to be regarded as merely exemplary.Accordingly, those of ordinary skill in the art will recognize thatvarious changes and modifications of the various embodiments describedherein can be made without departing from the scope and spirit of thedisclosure. In addition, descriptions of well-known functions andconstructions may be omitted for clarity and conciseness.

The terms and words used in the following description and claims are notlimited to the bibliographical meanings, but, are merely used by theinventor to enable a clear and consistent understanding of thedisclosure. Accordingly, it should be apparent to those skilled in theart that the following description of various embodiments of thedisclosure is provided for illustration purpose only and not for thepurpose of limiting the disclosure as defined by the appended claims andtheir equivalents.

It is to be understood that the singular forms “a,” “an,” and “the”include plural referents unless the context clearly dictates otherwise.Thus, for example, reference to “a component surface” includes referenceto one or more of such surfaces.

FIG. 1 is a block diagram of an electronic device 101 that providespersonalized biometric information based on a biometric signal in anetwork environment 100 according to various embodiments of thedisclosure.

Referring to FIG. 1 , the electronic device 101 in the networkenvironment 100 may communicate with an electronic device 102 via afirst network 198 (e.g., a short-range wireless communication network),or an electronic device 104 or a server 108 via a second network 199(e.g., a long-range wireless communication network). According to anembodiment, the electronic device 101 may communicate with theelectronic device 104 via the server 108. According to an embodiment,the electronic device 101 may include a processor 120, memory 130, aninput device 150, a sound output device 155, a display device 160, anaudio module 170, a sensor module 176, an interface 177, a haptic module179, a camera module 180, a power management module 188, a battery 189,a communication module 190 (e.g., a transceiver), a subscriberidentification module (SIM) 196, or an antenna module 197. In someembodiments, at least one (e.g., the display device 160 or the cameramodule 180) of the components may be omitted from the electronic device101, or one or more other components may be added in the electronicdevice 101. In some embodiments, some of the components may beimplemented as single integrated circuitry. For example, the sensormodule 176 (e.g., a fingerprint sensor, an iris sensor, or anilluminance sensor) may be implemented as embedded in the display device160 (e.g., a display).

The processor 120 may execute, for example, software (e.g., a program140) to control at least one other component (e.g., a hardware orsoftware component) of the electronic device 101 coupled with theprocessor 120, and may perform various data processing or computation.According to one embodiment, as at least part of the data processing orcomputation, the processor 120 may load a command or data received fromanother component (e.g., the sensor module 176 or the communicationmodule 190) in volatile memory 132, process the command or the datastored in the volatile memory 132, and store resulting data innon-volatile memory 134. According to an embodiment, the processor 120may include a main processor 121 (e.g., a central processing unit (CPU)or an application processor (AP)), and an auxiliary processor 123 (e.g.,a graphics processing unit (GPU), an image signal processor (ISP), asensor hub processor, or a communication processor (CP)) that isoperable independently from, or in conjunction with, the main processor121. Additionally or alternatively, the auxiliary processor 123 may beadapted to consume less power than the main processor 121, or to bespecific to a specified function. The auxiliary processor 123 may beimplemented as separate from, or as part of the main processor 121.

The auxiliary processor 123 may control at least some of functions orstates related to at least one component (e.g., the display device 160,the sensor module 176, or the communication module 190) among thecomponents of the electronic device 101, instead of the main processor121 while the main processor 121 is in an inactive (e.g., sleep) state,or together with the main processor 121 while the main processor 121 isin an active state (e.g., executing an application). According to anembodiment, the auxiliary processor 123 (e.g., an image signal processoror a communication processor) may be implemented as part of anothercomponent (e.g., the camera module 180 or the communication module 190)functionally related to the auxiliary processor 123.

The memory 130 may store various data used by at least one component(e.g., the processor 120 or the sensor module 176) of the electronicdevice 101. The various data may include, for example, software (e.g.,the program 140) and input data or output data for a command relatedthereto. The memory 130 may include the volatile memory 132 or thenon-volatile memory 134.

The program 140 may be stored in the memory 130 as software, and mayinclude, for example, an operating system (OS) 142, middleware 144, oran application 146.

The input device 150 may receive a command or data to be used by othercomponent (e.g., the processor 120) of the electronic device 101, fromthe outside (e.g., a user) of the electronic device 101. The inputdevice 150 may include, for example, a microphone, a mouse, or akeyboard.

The sound output device 155 may output sound signals to the outside ofthe electronic device 101. The sound output device 155 may include, forexample, a speaker or a receiver. The speaker may be used for generalpurposes, such as playing multimedia or playing record, and the receivermay be used for an incoming call. According to an embodiment, thereceiver may be implemented as separate from, or as part of the speaker.

The display device 160 may visually provide information to the outside(e.g., a user) of the electronic device 101. The display device 160 mayinclude, for example, a display, a hologram device, or a projector andcontrol circuitry to control a corresponding one of the display,hologram device, and projector. According to an embodiment, the displaydevice 160 may include touch circuitry adapted to detect a touch, orsensor circuitry (e.g., a pressure sensor) adapted to measure theintensity of force incurred by the touch.

The audio module 170 may convert a sound into an electrical signal andvice versa. According to an embodiment, the audio module 170 may obtainthe sound via the input device 150, or output the sound via the soundoutput device 155 or a headphone of an external electronic device (e.g.,an electronic device 102) directly (e.g., wiredly) or wirelessly coupledwith the electronic device 101.

The sensor module 176 may detect an operational state (e.g., power ortemperature) of the electronic device 101 or an environmental state(e.g., a state of a user) external to the electronic device 101, andthen generate an electrical signal or data value corresponding to thedetected state. According to an embodiment, the sensor module 176 mayinclude, for example, a gesture sensor, a gyro sensor, an atmosphericpressure sensor, a magnetic sensor, an acceleration sensor, a gripsensor, a proximity sensor, a color sensor, an infrared (IR) sensor, abiometric sensor, a temperature sensor, a humidity sensor, or anilluminance sensor.

The interface 177 may support one or more specified protocols to be usedfor the electronic device 101 to be coupled with the external electronicdevice (e.g., the electronic device 102) directly (e.g., wiredly) orwirelessly. According to an embodiment, the interface 177 may include,for example, a high definition multimedia interface (HDMI), a universalserial bus (USB) interface, a secure digital (SD) card interface, or anaudio interface.

A connecting terminal 178 may include a connector via which theelectronic device 101 may be physically connected with the externalelectronic device (e.g., the electronic device 102). According to anembodiment, the connecting terminal 178 may include, for example, a HDMIconnector, a USB connector, a SD card connector, or an audio connector(e.g., a headphone connector).

The haptic module 179 may convert an electrical signal into a mechanicalstimulus (e.g., a vibration or a movement) or electrical stimulus whichmay be recognized by a user via his tactile sensation or kinestheticsensation. According to an embodiment, the haptic module 179 mayinclude, for example, a motor, a piezoelectric element, or an electricstimulator.

The camera module 180 may capture a still image or moving images.According to an embodiment, the camera module 180 may include one ormore lenses, image sensors, image signal processors, or flashes.

The power management module 188 may manage power supplied to theelectronic device 101. According to one embodiment, the power managementmodule 188 may be implemented as at least part of, for example, a powermanagement integrated circuit (PMIC).

The battery 189 may supply power to at least one component of theelectronic device 101. According to an embodiment, the battery 189 mayinclude, for example, a primary cell which is not rechargeable, asecondary cell which is rechargeable, or a fuel cell.

The communication module 190 may support establishing a direct (e.g.,wired) communication channel or a wireless communication channel betweenthe electronic device 101 and the external electronic device (e.g., theelectronic device 102, the electronic device 104, or the server 108) andperforming communication via the established communication channel. Thecommunication module 190 may include one or more communicationprocessors that are operable independently from the processor 120 (e.g.,the application processor (AP)) and supports a direct (e.g., wired)communication or a wireless communication. According to an embodiment,the communication module 190 may include a wireless communication module192 (e.g., a cellular communication module, a short-range wirelesscommunication module, or a global navigation satellite system (GNSS)communication module) (e.g., a wireless transceiver) or a wiredcommunication module 194 (e.g., a local area network (LAN) communicationmodule or a power line communication (PLC) module) (e.g., a wiredtransceiver). A corresponding one of these communication modules maycommunicate with the external electronic device via the first network198 (e.g., a short-range communication network, such as Bluetooth™,wireless-fidelity (Wi-Fi) direct, or infrared data association (IrDA))or the second network 199 (e.g., a long-range communication network,such as a cellular network, the Internet, or a computer network (e.g.,local area network (LAN) or wide area network (WAN)). These varioustypes of communication modules may be implemented as a single component(e.g., a single chip), or may be implemented as multi components (e.g.,multi chips) separate from each other. The wireless communication module192 may identify and authenticate the electronic device 101 in acommunication network, such as the first network 198 or the secondnetwork 199, using subscriber information (e.g., international mobilesubscriber identity (IMSI)) stored in the subscriber identificationmodule 196.

The antenna module 197 may transmit or receive a signal or power to orfrom the outside (e.g., the external electronic device) of theelectronic device 101. According to an embodiment, the antenna module197 may include one or more antennas, and, therefrom, at least oneantenna appropriate for a communication scheme used in the communicationnetwork, such as the first network 198 or the second network 199, may beselected, for example, by the communication module 190 (e.g., thewireless communication module 192). The signal or the power may then betransmitted or received between the communication module 190 and theexternal electronic device via the selected at least one antenna.According to an embodiment, another component (e.g., a radio frequencyintegrated circuit (RFIC)) other than the radiating element may beadditionally formed as part of the antenna module 197.

At least some of the above-described components may be coupled mutuallyand communicate signals (e.g., commands or data) therebetween via aninter-peripheral communication scheme (e.g., a bus, general purposeinput and output (GPIO), serial peripheral interface (SPI), or mobileindustry processor interface (MIPI)).

According to an embodiment, commands or data may be transmitted orreceived between the electronic device 101 and the external electronicdevice 104 via the server 108 coupled with the second network 199. Eachof the electronic devices 102 and 104 may be a device of a same type as,or a different type, from the electronic device 101. According to anembodiment, all or some of operations to be executed at the electronicdevice 101 may be executed at one or more of the external electronicdevices 102, 104, or 108. For example, if the electronic device 101should perform a function or a service automatically, or in response toa request from a user or another device, the electronic device 101,instead of, or in addition to, executing the function or the service,may request the one or more external electronic devices to perform atleast part of the function or the service. The one or more externalelectronic devices receiving the request may perform the at least partof the function or the service requested, or an additional function oran additional service related to the request, and transfer an outcome ofthe performing to the electronic device 101. The electronic device 101may provide the outcome, with or without further processing of theoutcome, as at least part of a reply to the request. To that end, acloud computing, distributed computing, or client-server computingtechnology may be used, for example.

FIG. 2 is a block diagram 200 illustrating an electronic device thatprovides personalized biometric information based on a biometric signalaccording to various embodiments of the disclosure.

Referring to FIG. 2 , an electronic device 201 (e.g., the electronicdevice 101 of FIG. 1 ) may include a wireless communication circuit 210(e.g., the wireless communication module 192 in FIG. 1 ), a memory 220(e.g., the memory 130 in FIG. 1 ), a touch screen display 230 (e.g., thedisplay device 160 in FIG. 1 ), a sensor module 240 (e.g., the sensormodule 176 in FIG. 1 ), and a processor 250 (e.g., the processor 120 inFIG. 1 ).

In an embodiment, the electronic device 201 may be a wearable device.

In an embodiment, the wireless communication circuit 210 may establishcommunications between the electronic device 201 and external electronicdevice (e.g., the electronic devices 102 and 104, the server 108 in FIG.1 ).

In an embodiment, the electronic device 201 may transmit biometricinformation of a user (e.g., biometric signals, biometric states, etc.)obtained through the sensor module 240 to an external electronic devicethrough the wireless communication circuit 210. The external electronicdevice may store the biometric information of the user received from theelectronic device 201.

In an embodiment, the electronic device 201 may receive, from theexternal electronic device, external information, which is a referencefor determining a reference value for the biometric signal, through thewireless communication circuit 210. The external information may includedemographic information. For example, the demographic information mayinclude information such as gender, age, climate, race, and the like.

In an embodiment, the memory 220 may store a program for measuringuser's biometric signals, a program for determining a personalizedreference value on the basis of the user's biometric signals, and aprogram for determining the biometric state of the user on the basis ofthe same.

In an embodiment, the memory 220 may store a reference value fordetermining the activity state of the user. For example, the memory 220may store reference patterns for the activity state of the user, such asa dynamic state, a static state (e.g., a static stable state or a staticunstable state), and a stable state.

In an embodiment, the memory 220 may store biometric information of theuser (e.g., biometric signals, biometric states, etc.) obtained throughthe sensor module 240.

In an embodiment, the touch screen display 230 may be configured as anintegral unit including a display 231 and a touch panel 233.

In an embodiment, the touch screen display 230 may display sensorinformation of the user (e.g., heart rate (HR), blood pressure (BP), andthe like), which is obtained from the sensor module 240 under thecontrol of the processor 250. The touch screen display 230 may displayinformation related to the biometric state of the user under the controlof the processor 250. For example, the information related to thebiometric state of the user may include health information, stressinformation, blood pressure information, and the like. The touch screendisplay 230 may output the information related to the biometric state ofthe user in the form of a message, a pop-up window, or the like underthe control of the processor 250. However, the disclosure is not limitedthereto, and the information related to the biometric state of the usermay be output as a sound through a speaker (e.g., the sound outputdevice 155 in FIG. 1 ).

In an embodiment, the sensor module 240 may include a biometric sensor(e.g., a photoplethysmography (PPG) sensor or a skin temperaturesensor), an acceleration sensor, and the like.

In an embodiment, the sensor module 240 (e.g., the acceleration sensor)may detect the motion of the electronic device 201. The sensor module240 may transmit a sensor signal according to the motion of theelectronic device 201 to the processor 250.

In an embodiment, the sensor module 240 (e.g., the PPG sensor) mayobtain a continuous PPG value. For example, the PPG value may include aheart rate, a blood pressure, and the like. The sensor module 240 maytransmit the obtained PPG value to the processor 250.

In an embodiment, the processor 250 may control the overall operation ofthe electronic device 201 and signal flows between internal componentsof the electronic device 201, may perform data processing, and maycontrol power supply from a battery (e.g., the battery 189 in FIG. 1 )to the above components.

In an embodiment, the processor 250 may obtain at least one biometricsignal through the sensor module 240 at a predetermined time interval.The processor 250 may determine the activity state of the user (e.g., adynamic state (e.g., walking or running), a static state (e.g., a staticstable state or a static unstable state), and a stable state) on thebasis of at least one biometric signal obtained from the sensor module240.

In an embodiment, the processor 250 may compare a predetermined motionpattern for the activity state of the user, which is stored in thememory 220, with a motion pattern of the electronic device 201, which ismeasured through the sensor module 240 (e.g., the acceleration sensor).The processor 250 may determine the activity state of the user on thebasis of the comparison result. The processor 250 may compare apredetermined sensor value for the activity state of the user, which isstored in the memory 220, with a PPG sensor value obtained through thesensor module 240 (e.g., the PPG sensor or the skin temperature sensor).The processor 250 may determine the activity state of the user on thebasis of the comparison result.

In an embodiment, the processor 250 may determine the activity state ofthe user on the basis of a change in the biometric signal.

In an embodiment, the processor 250 may determine whether or not theuser is in the stable state on the basis of at least one of the patterncomparison or a change in the biometric signal. If the user is in thestable state, the processor 250 may obtain a representative value forthe respective of the at least one biometric signal. The processor 250may define the obtained representative value for the respective of theat least one biometric signal as a candidate reference value for acorresponding biometric signal. For example, the representative valuefor the respective of the at least one biometric signal may include oneof a minimum value, a maximum value, an average value, a mode value, amedian value, an interval initial value, and a final value for therespective of the at least one biometric signal.

In an embodiment, if the user is determined to be in the stable state,the processor 250 may store, in the memory 220, the respective of the atleast one biometric signal (e.g., heart rate, heart rate variation, andblood pressure values) in the interval of the stable state.

In an embodiment, the processor 250 may determine a candidate referencevalue that satisfies a predetermined condition as a first referencevalue for the corresponding biometric signal. For example, thepredetermined condition may include at least one of whether or not thecandidate reference value is included within a specific range of thehistogram for each biometric signal in the stable state, which has beenobtained recently for a predetermined period of time, or whether or notthe candidate reference value is included within a specific range ofexternal information (e.g., demographic information).

In an embodiment, the processor 250 may update a second reference value,which was previously configured for the corresponding biometric signal,on the basis of the first reference value.

In an embodiment, the processor 250 may compare a value of at least onebiometric signal obtained from the sensor module 240 with a referencevalue corresponding to the at least one biometric signal. The processor250 may provide a notification of personalized information related tothe biometric state of the user determined on the basis of thecomparison result. The personalized information related to the biometricstate of the user may include health information, stress information,blood pressure information, and the like. The processor 250 may providethe personalized information related to the biometric state of the userin the form of at least one of a message, a pop-up window, or a sound.

FIG. 3 is a flowchart 300 explaining a method for providing personalizedbiometric information based on a biometric signal according to variousembodiments of the disclosure.

Referring to FIG. 3 , the processor (e.g., the processor 250 in FIG. 2 )may obtain biometric signals in operation 310. For example, theprocessor may obtain at least one biometric signal from the sensormodule (e.g., the sensor module 240 in FIG. 2 ). For example, the atleast one biometric signal may include a continuous PPG value obtainedfrom a sensor module, such as a PPG sensor, a continuous skintemperature value obtained from a skin temperature sensor, and acontinuous acceleration value for the motion of the electronic device(e.g., the electronic device 201 in FIG. 2 ) obtained from anacceleration sensor.

In an embodiment, the processor may determine the activity state of auser in operation 320. The processor may determine the activity state ofthe user on the basis of at least one biometric signal obtained from thesensor module. For example, the activity state of the user may include adynamic state, a static state (e.g., a static stable state or a staticunstable state), and a stable state.

In an embodiment, a reference pattern for the activity state of theuser, such as a dynamic state, a static state (e.g., a static stablestate or a static unstable state), or a stable state, may be pre-storedin the memory (e.g., the memory 220 in FIG. 2 ).

In an embodiment, the processor may determine the activity state of theuser by comparing the reference pattern of the activity state of theuser, which was pre-stored in memory, with at least one biometric signalobtained from the sensor module.

In an embodiment, the processor may extract candidate reference valuesfor the biometric signals in operation 330. In operation 330 describedabove, if the activity state of the user is determined to be a stablestate, the processor may extract representative values for therespective biometric signal values in the interval during which theactivity state of the user is determined to be a stable state. Theprocessor may define the extracted representative values for therespective biometric signal values as candidate reference value for thecorresponding biometric signal.

In an embodiment, the processor may determine a reference value for thebiometric signal in operation 340. The processor may determine acandidate reference value that satisfies a predetermined condition,among the defined candidate reference values for the correspondingbiometric signal, as a reference value for the corresponding biometricsignal. For example, the predetermined condition may include at leastone of a histogram or external information (e.g., demographicinformation).

In an embodiment, the processor may determine a candidate referencevalue satisfying at least one of a specific range of the histogram orthe external information, among the candidate reference values for thecorresponding biometric signal, as a reference value for thecorresponding biometric signal.

In an embodiment, the processor may update a reference value for thebiometric signal in operation 350. The processor may update a referencevalue, which was previously configured for the corresponding biometricsignal, on the basis of the reference value determined in operation 340.

In an embodiment, the processor may determine the biometric state of theuser in operation 360. The processor may compare the reference value forthe biometric signal, which is updated in operation 350, with at leastone biometric signal obtained from the sensor module, therebydetermining the biometric state of the user on the basis of the same.

In an embodiment, the processor may provide a notification related tothe biometric state of the user in operation 370. The processor mayprovide a notification of information related to the biometric state ofthe user on the basis of the biometric state of the user determined inoperation 360. For example, the information related to the biometricstate of the user may include a user's stress level and the like.

In an embodiment, the above-described operations in FIG. 3 will bedescribed in detail with reference to FIGS. 4 to 6 .

FIG. 4 is a flowchart 400 explaining a method for determining areference value for providing personalized biometric information basedon a biometric signal according to various embodiments of thedisclosure.

Referring to FIG. 4 , a processor (e.g., the processor 250 in FIG. 2 )may obtain at least one biometric signal through a sensor module (e.g.,the sensor module 240 in FIG. 2 ) at a predetermined time interval inoperation 401.

In an embodiment, the processor may monitor the sensor module providedin the electronic device (e.g., the electronic device 201 in FIG. 2 ),thereby obtaining at least one biometric signal. For example, the sensormodule may include a biometric sensor (e.g., a PPG sensor or a skintemperature sensor), an acceleration sensor, and the like.

In an embodiment, the processor may obtain a continuous PPG value, suchas a heart rate value, a blood pressure value, or the like, from thebiometric sensor (e.g., the PPG sensor). The processor may obtain acontinuous skin temperature value from the biometric sensor (e.g., theskin temperature sensor). The processor may obtain a continuousacceleration value for the motion of the electronic device through theacceleration sensor.

In an embodiment, the processor may determine whether or not the user isin the stable state on the basis of at least one biometric signalobtained from the sensor module in operation 403.

In an embodiment, the processor may analyze a motion pattern of theelectronic device using an acceleration value measured through theacceleration sensor. The processor may determine the activity state ofthe user (e.g., a dynamic state (e.g., walking or running) or a staticstate (e.g., a static stable state or a static unstable state)) on thebasis of the motion pattern of the electronic device.

In an embodiment, the motion pattern for the activity state of the usermay be predefined, and may be stored in the memory (e.g., the memory 220in FIG. 2 ).

In an embodiment, the processor may compare the predefined motionpattern stored in the memory with the motion pattern of the electronicdevice, which is measured through the acceleration sensor, therebydetermining the activity state of the user on the basis of the same.

In an embodiment, if a user's motion is detected through theacceleration sensor, the processor may determine that the electronicdevice is in a dynamic state. For example, the dynamic state may includean exercise state of the user (e.g., walking or running).

In an embodiment, the processor may obtain a biometric signal through abiometric sensor.

In an embodiment, if the user is in the exercise state, the obtainedbiometric signal may vary. For example, if the user is in the exercisestate, the user's heart rate or skin temperature may increase.

In an embodiment, if no motion of the electronic device is detectedthrough the acceleration sensor, and if the changed state of thebiometric signal is maintained for a predetermined period of time, theprocessor may determine that the user is in a static stable state.

In an embodiment, the example in which no motion of the electronicdevice is detected may include the case where the user has finished theexercise, such as walking, running, and the like.

In an embodiment, if no motion of the electronic device is detected, butif the heart rate is increased, or if the increased heart rate ismaintained for a predetermined period of time due to an oxygen debtimmediately after exercise, the processor may determine that the user isin a static unstable state.

In an embodiment, if no motion of the electronic device is detectedthrough the acceleration sensor, and if the biometric signal obtainedthrough the biometric sensor is increased, compared to a predefinedbiometric signal, the processor may determine that the user is in astatic unstable state. For example, the static unstable state mayinclude the states in which the heart rate and the blood pressure areincreased and the skin temperature is reduced due to emotional awakeningand stress, in which the heart rate is increased and the blood pressureis reduced due to drinking, and in which the heart rate and the bloodpressure are increased due to smoking.

In an embodiment, if the user is not in the dynamic state and the staticstate (e.g., the static stable state or the static unstable state), theprocessor may determine that the user is in the stable state. Forexample, if a user's motion and a biometric signal (e.g., a change inthe heart rate and the blood pressure) are not detected for apredetermined period of time, the processor may determine that the useris in the stable state.

In an embodiment, if the user is in the stable state, the processor mayobtain representative value for each at least one biometric signal, andmay define the obtained representative value as candidate referencevalue for the corresponding biometric signal in operation 405.

In an embodiment, if the stable state of the user is maintained for apredetermined period of time, the processor may obtain representativevalue for respective biometric signals in the interval during which theuser is determined to be in the stable state. The processor maydetermine the obtained representative values for the respectivebiometric signals as candidate reference values for the one or morebiometric signals.

In an embodiment, the representative values for the respective biometricsignals in the interval during which the user is determined to be in thestable state may include one of a minimum value, a maximum value, anaverage value, a mode value, a median value, an interval initial value,and a final value for the respective biometric signals.

In an embodiment, if the user is determined to be in the stable state,the processor may store, in the memory, respective biometric signalvalues, such as a heart rate value, a heart rate variation, and a bloodpressure value, in the stable-state interval.

In an embodiment, the processor may determine a candidate referencevalue that satisfies a predetermined condition as a first referencevalue for the corresponding biometric signal in operation 407.

In an embodiment, the predetermined condition may include at least oneof whether or not the candidate reference value is included within aspecific range of a histogram for each biometric signal in the stablestate, which has recently been obtained for a predetermined period oftime, or whether or not the candidate reference value is included withina specific range of demographic information.

In an embodiment, the processor may configure a specific range on thehistogram that records each biometric signal in the stable state, andmay determine whether or not the candidate reference value of eachbiometric signal is included within a reference range on the histogramthat records each biometric signal.

In an embodiment, if the candidate reference value of each biometricsignal is included within a specific range on the histogram for eachbiometric signal, the processor may determine the candidate referencevalue to be a first reference value for the corresponding biometricsignal.

In an embodiment, the rage of the reference value based on thedemographic information may include a reference range that can beobtained on the basis of references, such as age, gender, and the like.

In an embodiment, if the candidate reference value of each biometricsignal is included within the range of the reference value based on thedemographic information, the processor may determine the biometricsignal reference value included in the range of the reference valuebased on demographic information as the first reference value.

In an embodiment, the processor may update a second reference value,which was previously configured for the corresponding biometric signal,on the basis of the first reference value in operation 409.

In an embodiment, the updated reference value may be used as a referencevalue for determining the biometric state of the user (e.g., a stresslevel) on the basis of each of obtained at least one biometric signal.

FIG. 5 is a flowchart 500 explaining a method for determining areference value for providing personalized biometric information basedon a biometric signal according to various embodiments of thedisclosure.

In an embodiment, FIG. 5 embodies the respective operations in FIG. 4described above, and the operations in FIG. 5 , which are similar tothose in FIG. 4 , may refer to the description related to FIG. 4 .

Referring to FIG. 5 , a processor (e.g., the processor 250 in FIG. 2 )may obtain at least one biometric signal through a sensor module (e.g.,the sensor module 240 in FIG. 2 ) at a predetermined time interval inoperation 501.

In an embodiment, the sensor module may include a biometric sensor(e.g., a PPG sensor or a skin temperature sensor), an accelerationsensor, and the like.

In an embodiment, the processor may obtain a continuous PPG value, suchas a heart rate value, a blood pressure value, or the like, from thebiometric sensor (e.g., the PPG sensor). The processor may obtain acontinuous skin temperature value from the biometric sensor (e.g., theskin temperature sensor). The processor may obtain a continuousacceleration value for the motion of the electronic device detected bythe acceleration sensor.

In an embodiment, the processor may analyze a change in at least onebiometric signal in operation 503, and may determine whether or not theuser is in a first state in operation 505.

In an embodiment, the first state may include a static state. In anembodiment, the static state may include a static stable state and astatic unstable state.

In an embodiment, the static state (e.g., the static stable state) mayinclude the case where a heart rate value or a blood pressure value,which was increased due to the motion of the electronic device, ismaintained for a predetermined period of time.

In an embodiment, the static state (e.g., the static unstable state) mayinclude at least one of the case where a biometric signal value obtainedfrom the biometric sensor is increased relative to a predefinedbiometric signal value in the state in which no motion of the electronicdevice is detected or the case where the increased state in thebiometric signal value is maintained for a predetermined period of time.

In an embodiment, Equation 1 below represents a condition fordetermining whether or not the user is in a first state (e.g., thestatic state). Although the following embodiments will be described onthe assumption that the biometric signal denotes heart rate (HR), theembodiments are not limited thereto, and the biometric signal may denoteblood pressure (BP).

$\begin{matrix}{\frac{{{HR}( t_{i} )} - {{HR}( {t_{i} - {\Delta\; T}} )}}{\Delta\; t} > \tau_{HR}} & {{Equation}\mspace{14mu} 1}\end{matrix}$

In an embodiment, each interval T_(i) may be defined as a period of timeΔT from time (t_(i)−ΔT) to time (t_(i)). In an embodiment, thedifference between the end time points of two consecutive intervals maybe (t_((i+1)−t_(i))=dt>0. In an embodiment, when 0<dt<ΔT, the twointervals may overlap each other.

In an embodiment, if the interval during which the heart rate (or bloodpressure) increases, the interval during which the increased state ofthe heart rate (or blood pressure) is maintained for a predeterminedperiod of time, and the interval during which the increased heart rate(or blood pressure) decreases are detected in the state in which nomotion of the electronic device is detected, the processor may determinethat the user is in a static state (e.g., a static unstable state).

For example, if the heart rate in the interval T_(i) satisfies Equation1 (for example, if the incremental slope of the biometric signal exceedsa specific value τ_(HR)), the processor may determine the interval T_(i)as an “increasing interval”, and may determine that the user is in astatic state (e.g., a static unstable state).

In an embodiment, for example, if T₀ is determined as an increasingpoint, and if the difference between a representative value of thebiometric signal for all intervals T_(i) (i=1, 2, . . . , L) from T₁ tothe current interval T_(L) and a representative value for the intervalT⁻¹ before entering the increasing point exceeds a predetermined value,the processor may determine the intervals T₁ to T_(L) to be in a staticstate (e.g., a static unstable state).

In an embodiment, if the user is in a first state, the processor maydetermine whether or not the user is in a second state in operation 507.

In an embodiment, the second state may include a stable state.

In an embodiment, the processor may determine whether or not the user isin the second state on the basis of at least one piece of biometricinformation, such as heart rate, heart rate variation, and bloodpressure values.

In an embodiment, if the user is in the second state, the processor maystore at least one biometric signal in the memory (e.g., the memory 220in FIG. 2 ) in operation 509. For example, the processor may store, inthe memory, each piece of biometric information, such as heart rate,heart rate variation, and blood pressure values, in the stable stateinterval.

In an embodiment, Equations 2 to 5 below may be used as a method forextracting the stable state interval.

In an embodiment, assuming that three-axis acceleration signals areACCx, ACCy, and ACCz, respectively, f_(motion) may be a featureindicating the magnitude of acceleration (∥ACC∥) extracted on the basisof the acceleration signal in the interval. The f_(motion) may includethe magnitude of acceleration (∥ACC∥), standard deviation σ(ACC), andthe like.

In an embodiment, the f_(motion) may be defined as acticount tocalculate the degree of motion for each interval. The acticount may bedefined as Equation 2 below.Acticount=Σ_(∥fACC(t)∥>Acticount) ₀ ∥fACC(t)∥  Equation 2

For example, the processor may obtain a magnitude value of anacceleration signal fACC filtered by a band-pass filter in order toremove signals other than the motion of the electronic device. Theprocessor may summate the obtained magnitude values of the filteredacceleration signals fACC, which are equal to or more than a predefinedActicount₀, thereby obtaining acticount.

In an embodiment, the processor may extract an interval during which amotion feature (e.g., the acticount) is equal to or less than apredetermined level for a predetermined period of time (e.g., n minutes)immediately before the current interval and during which no biometricsignal (e.g., the heart rate) is increased using the obtained degree ofmotion for each interval.

In an embodiment, in order to determine whether or not the extractedinterval corresponds to a stable state, the processor may measure arange of changes in the biometric signals, such as heart rate, bloodpressure, skin temperature, and the like, in the extracted interval.

In an embodiment, the processor may determine, as a stable state, theinterval during which the range of changes of the biometric signals doesnot exceed a predetermined range and is maintained for a predeterminedperiod of time.

In an embodiment, assuming that Δt is the minimum time unit for dividingeach interval, all intervals (e.g., T_(x) may be defined as I smallintervals having a period of time Δt.

The embodiment will be described on the assumption that, for example,the average value of the biometric signal (e.g., the heart rate) for thecurrent interval T_(L)=(t_(L)−ΔT˜t_(L)) is HR_(L) . As a result ofcalculation using Equations 3 and 4 below, if an interval in which thedifference in the biometric signal (e.g., the heart rate) between allconsecutive minimum time (Δt) units in the interval and the standarddeviation thereof are equal to or less than predetermined values(r_(HR1) and r_(HR2)) is detected, the processor may determine theinterval satisfying the condition of the predetermined values (r_(HR1)and r_(HR2)) to be a stable state interval.

$\begin{matrix}{{{{{HR}( {t_{L} - {(i)( {\Delta\; t} )}} )} - {{HR}( {t_{L} - {( {i + 1} )( {\Delta\; t} )}} )}} < r_{{HR}\; 1}},( {{i = 0},\ldots\;,{I - 1}} )} & {{Equation}\mspace{14mu} 3} \\{\sqrt{\frac{\sum_{i = {{0\sim I} - 1}}( {{{HR}( {t_{L} - {i\;\Delta\; t}} )} - \overset{\_}{HR}} )^{2}}{I}} < r_{{HR}\; 2}} & {{Equation}\mspace{14mu} 4}\end{matrix}$

In an embodiment, the processor may produce a histogram on the basis ofeach of the at least one biometric signal in operation 511. For example,the processor may produce a histogram for each of the at least onebiometric signal on the basis of each of the at least one biometricsignal for a second state (e.g., a stable state) of the user.

In an embodiment, the histogram for each of the at least one biometricsignal may be the accumulated data on each of the at least one biometricsignal, which have recently been obtained for a predetermined period oftime (e.g., 10 days).

In an embodiment, if the user is in a second state (e.g., a stablestate), the processor may obtain representative value for the respectiveof the at least one biometric signal, and may define the representativevalue as candidate biometric signal reference value for the of the atleast one respective biometric signal in operation 513, independentlyfrom operation 509 and operation 511 described above.

In an embodiment, Equation 5 below is intended to extract arepresentative value for each biometric signal in the interval that isdetermined as the second state (e.g., the stable state). In anembodiment, the function f{x} for extracting a representative value foreach biometric signal in the interval determined as the second state(e.g., the stable state) may be specified as one of an average value, amode value, and a median value. The processor may multiply the result ofa representative value function f{x} by a constant (e.g., C₁), and mayadd another constant (e.g., C₂) thereto, thereby obtaining a candidatereference value B*for the biometric signal (e.g., the heart rate).B _(i) *=C ₁ f{HR(T)}+C ₂  Equation 5

In an embodiment, the processor may determine the candidate biometricsignal reference value as a first reference value for the correspondingbiometric signal on the basis of at least one of the histogram orexternal information in operation 515.

For example, if the candidate reference value for the biometric signal(e.g., the heart rate) is included within the specific range of thehistogram produced in operation 511, the processor may determine thecandidate biometric reference value as a first reference value for thecorresponding biometric signal (e.g., the heart rate).

In an embodiment, the processor may use Equations 6 and 7 below in orderto reduce an error when determining the candidate reference value forthe biometric signal (e.g., a candidate reference value for the heartrate) as a first reference value for the corresponding biometric signal.

In an embodiment, if the obtained candidate reference value (e.g., B*)for the corresponding biometric signal (e.g., the heart rate) isincluded within a reference range of the entire data histogram (e.g., H)(e.g., a bin of upper 80% of the histogram) for each biometric signal ofthe user for a predetermined period of time (e.g., last 72 hours), andif the obtained candidate reference value (e.g., B*) is included withinthe range equal to or more than a reference percentage (e.g., ρ₂) basedon the representative value (e.g., H) (e.g., a mode value, a medianvalue, or an average value) of the histogram (e.g., the range within 80%of the average value of the histogram), the processor may determine thecandidate reference value (e.g., B*) for the biometric signal (e.g., theheart rate) as a first reference value for the biometric signal (e.g.,the heart rate).

$\begin{matrix}{\frac{\sum_{i = {{H{(i)}} > {H{(B^{*})}}}}{H(i)}}{\sum H} > \rho_{1}} & {{Equation}\mspace{14mu} 6} \\{{\overset{\_}{H} - h} \leq B^{*} \leq {\overset{\_}{H} + {h\mspace{14mu}{when}\mspace{14mu}\frac{\sum_{i = {\overset{\_}{H} - {h\sim\overset{\_}{H}} + h}}{H(j)}}{\sum H}}} > \rho_{2}} & {{Equation}\mspace{14mu} 7}\end{matrix}$

In an embodiment, if the value of the histogram bin to which thecandidate reference value B*for the corresponding biometric signal(e.g., heart rate) is equal to or more than a specific percentage of thetotal histogram sum, the processor may determine the candidate referencevalue B*for a biometric signal (e.g., heart rate) as a first referencevalue for heart rate.

In an embodiment, the first reference value for the biometric signal maybe determined on the basis of the external information.

In an embodiment, the external information may include demographicinformation. For example, the demographic information may includeinformation such as gender, age, climate, race, and the like. Forexample, the processor may determine a candidate reference valueincluded within a specific range of the demographic information, amongthe candidate reference values for the biometric signal (e.g., the heartrate), as a first reference value for the corresponding biometric signal(e.g., the heart rate).

In an embodiment, the processor may update a second reference value,which was previously configured for the corresponding biometric signal,on the basis of the determined first reference value in operation 517.

In an embodiment, the processor may apply predetermined weights (e.g., ωand (1−ω)) to the reference value B*(e.g., the first reference value) ofthe corresponding biometric signal and the reference value B (e.g., thesecond reference value), which was previously configured for thecorresponding biometric signal, as shown in Equation 8 below. Theprocessor may update the previously configured second reference valuewith the reference value B obtained by applying the weight thereto.B=ωB+(1−ω)B*  Equation 8

In an embodiment, Equations 1 to 8 are provided to facilitate thedescription of the respective operations and are intended fordetermining the activity state of the user, obtaining a candidatereference value for the biometric signal, determining a reference valuefor the biometric signal, and updating the reference value for thebiometric signal, but equations are not limited to Equations 1 to 8described above.

FIG. 6 is a flowchart 600 explaining a method for providing personalizedbiometric information based on a biometric signal according to variousembodiments of the disclosure.

Referring to FIG. 6 , a processor (e.g., the processor 250 in FIG. 2 )may obtain at least one biometric signal through a sensor module (e.g.,the sensor module 240 in FIG. 2 ) in operation 601.

In an embodiment, the processor may compare value of the obtained atleast one biometric signal with reference value corresponding to the atleast one biometric signal (e.g., the reference value B obtained usingEquation 8) in operation 603.

In an embodiment, the processor may provide a notification ofpersonalized information related to the biometric state of the userdetermined on the basis of the comparison result in operation 605.

In an embodiment, the personalized information related to the biometricstate of the user may include health information, stress information, BPinformation, and the like. In an embodiment, the personalizedinformation related to the biometric state of the user may be providedin the form of at least one of a message, a pop-up window, or a sound.For example, the personalized information related to the biometric stateof the user may include the content such as “Personalization of user'sbiometric signals is complete.”, “User is in stress level 4. You need abreak.”, and the like.

In an embodiment, the memory (e.g., the memory 220 in FIG. 2 ) may storeinstructions. In an embodiment, the operations related to FIGS. 1 to 6described above may be performed by a mechanism (e.g., a processor) thatcan read the instructions stored in the memory.

The electronic device according to various embodiments may be one ofvarious types of electronic devices. The electronic devices may include,for example, a portable communication device (e.g., a smart phone), acomputer device, a portable multimedia device, a portable medicaldevice, a camera, a wearable device, or a home appliance. According toan embodiment of the disclosure, the electronic devices are not limitedto those described above.

It should be appreciated that various embodiments of the disclosure andthe terms used therein are not intended to limit the technologicalfeatures set forth herein to particular embodiments and include variouschanges, equivalents, or replacements for a corresponding embodiment.With regard to the description of the drawings, similar referencenumerals may be used to refer to similar or related elements. It is tobe understood that a singular form of a noun corresponding to an itemmay include one or more of the things, unless the relevant contextclearly indicates otherwise. As used herein, each of such phrases as “Aor B,” “at least one of A and B,” “at least one of A or B,” “A, B, orC,” “at least one of A, B, and C,” and “at least one of A, B, or C,” mayinclude any one of, or all possible combinations of the items enumeratedtogether in a corresponding one of the phrases. As used herein, suchterms as “1st” and “2nd,” or “first” and “second” may be used to simplydistinguish a corresponding component from another, and does not limitthe components in other aspect (e.g., importance or order). It is to beunderstood that if an element (e.g., a first element) is referred to,with or without the term “operatively” or “communicatively”, as “coupledwith,” “coupled to,” “connected with,” or “connected to” another element(e.g., a second element), it means that the element may be coupled withthe other element directly (e.g., wiredly), wirelessly, or via a thirdelement.

As used herein, the term “module” may include a unit implemented inhardware, software, or firmware, and may interchangeably be used withother terms, for example, “logic,” “logic block,” “part,” or“circuitry”. A module may be a single integral component, or a minimumunit or part thereof, adapted to perform one or more functions. Forexample, according to an embodiment, the module may be implemented in aform of an application-specific integrated circuit (ASIC).

Various embodiments as set forth herein may be implemented as software(e.g., the program 140) including one or more instructions that arestored in a storage medium (e.g., internal memory 136 or external memory138) that is readable by a machine (e.g., the electronic device 101).For example, a processor (e.g., the processor 120) of the machine (e.g.,the electronic device 101) may invoke at least one of the one or moreinstructions stored in the storage medium, and execute it, with orwithout using one or more other components under the control of theprocessor. This allows the machine to be operated to perform at leastone function according to the at least one instruction invoked. The oneor more instructions may include a code generated by a compiler or acode executable by an interpreter. The machine-readable storage mediummay be provided in the form of a non-transitory storage medium. Wherein,the term “non-transitory” simply means that the storage medium is atangible device, and does not include a signal (e.g., an electromagneticwave), but this term does not differentiate between where data issemi-permanently stored in the storage medium and where the data istemporarily stored in the storage medium.

According to an embodiment, a method according to various embodiments ofthe disclosure may be included and provided in a computer programproduct. The computer program product may be traded as a product betweena seller and a buyer. The computer program product may be distributed inthe form of a machine-readable storage medium (e.g., compact disc readonly memory (CD-ROM)), or be distributed (e.g., downloaded or uploaded)online via an application store (e.g., Play Store™), or between two userdevices (e.g., smart phones) directly. If distributed online, at leastpart of the computer program product may be temporarily generated or atleast temporarily stored in the machine-readable storage medium, such asmemory of the manufacturer's server, a server of the application store,or a relay server.

According to various embodiments, each component (e.g., a module or aprogram) of the above-described components may include a single entityor multiple entities. According to various embodiments, one or more ofthe above-described components may be omitted, or one or more othercomponents may be added. Alternatively or additionally, a plurality ofcomponents (e.g., modules or programs) may be integrated into a singlecomponent. In such a case, according to various embodiments, theintegrated component may still perform one or more functions of each ofthe plurality of components in the same or similar manner as they areperformed by a corresponding one of the plurality of components beforethe integration. According to various embodiments, operations performedby the module, the program, or another component may be carried outsequentially, in parallel, repeatedly, or heuristically, or one or moreof the operations may be executed in a different order or omitted, orone or more other operations may be added.

While the disclosure has been shown and described with reference tovarious embodiments thereof, it will be understood by those skilled inthe art that various changes in form and details may be made thereinwithout departing from the spirit and scope of the disclosure as definedby the appended claims and their equivalents.

What is claimed is:
 1. An electronic device comprising: an accelerationsensor; a biometric sensor; and at least one processor operativelyconnected to the acceleration sensor and the biometric sensor, whereinthe at least one processor is configured to: identify a state of theelectronic device based on motion information of the electronic deviceobtained through the acceleration sensor, obtain a first value of afirst biometric signal measured through the biometric sensor in casethat the identified state of the electronic device is a state of nomotion, compare the obtained first value of the first biometric signalwith a reference value corresponding to the first biometric signal, thereference value being determined at least based on demographicinformation including at least one of a user's gender, age, or race, andbased on a result of the comparing, provide a notification related tothe first biometric signal, wherein the at least one processor isfurther configured to: obtain a second value of the first biometricsignal measured through the biometric sensor in case that the identifiedstate of the electronic device is the state of no motion, and update thereference value based on the second value of the first biometric signal.2. The electronic device of claim 1, wherein the at least one processoris further configured to: identify a state of a user based on at leastone biometric signal obtained through the biometric sensor, wherein theat least one biometric signal is other than the first biometric signal,and obtain the second value of the first biometric signal measuredthrough the biometric sensor in case that the identified state of theelectronic device is the state of no motion and the identified state ofthe user is a state where a value of the at least one biometric signalis maintained for a predetermined period of time within a predeterminedrange.
 3. The electronic device of claim 2, wherein the at least oneprocessor is further configured to store the second value of the firstbiometric signal in a memory of the electronic device.
 4. The electronicdevice of claim 2, wherein the at least one processor is furtherconfigured to: based on the second value of the first biometric signalsatisfying a predetermined condition, update the reference value to bethe second value of the first biometric signal.
 5. The electronic deviceof claim 4, wherein the at least one processor is further configured toproduce a histogram for the first biometric signal.
 6. The electronicdevice of claim 5, wherein the predetermined condition comprises atleast one of the histogram for the first biometric signal or externalinformation.
 7. The electronic device of claim 6, further comprising: awireless communication circuit, wherein the at least one processor isfurther configured to receive the external information through thewireless communication circuit, and wherein the external informationcomprises the demographic information.
 8. The electronic device of claim6, wherein the at least one processor is further configured to:determine that the second value of the first biometric signal isincluded within a specific range of at least one of the histogram or theexternal information, and based on determining that the second value ofthe first biometric signal is included within the specific range, updatethe reference value to be the second value of the first biometricsignal.
 9. The electronic device of claim 5, wherein the histogram forthe first biometric signal comprises a histogram of accumulated data forthe first biometric signal obtained for a predetermined period of time.10. The electronic device of claim 1, wherein the at least one processoris further configured to: based on the result of the comparing, provideinformation related to a stress level in a form of at least one of amessage, a pop-up window, or a sound.
 11. A method of providingpersonalized biometric information based on a biometric signal, themethod comprising: identifying a state of an electronic device based onmotion information of the electronic device obtained through anacceleration sensor; obtaining a first value of a first biometric signalmeasured through a biometric sensor in case that the identified state ofthe electronic device is in a state of no motion; comparing the obtainedfirst value of the first biometric signal with a reference valuecorresponding to the first biometric signal, the reference value beingdetermined at least based on demographic information including at leastone of a user's gender, age, or race; and based on a result of thecomparing, providing a notification related to the first biometricsignal, wherein the method further comprises: obtaining a second valueof the first biometric signal measured through the biometric sensor incase that the identified state of the electronic device is the state ofno motion; and updating the reference value based on the second value ofthe first biometric signal.
 12. The method of claim 11, furthercomprising: identifying a state of a user based on at least onebiometric signal obtained through the biometric sensor, wherein the atleast one biometric signal is other than the first biometric signal; andobtaining the second value of the first biometric signal measuredthrough the biometric sensor in case that the identified state of theelectronic device is the state of no motion and the identified state ofthe user is a state where a value of the at least one biometric signalis maintained for a predetermined period of time within a predeterminedrange.
 13. The method of claim 12, further comprising: storing thesecond value of the first biometric signal in a memory of the electronicdevice.
 14. The method of claim 12, wherein the determining of thesecond value of the first biometric signal as the reference valuecomprises: based on the second value of the first biometric signalsatisfying a predetermined condition, updating the reference value to bethe second value of the first biometric signal.
 15. The method of claim14, further comprising: producing a histogram for the first biometricsignal.
 16. The method of claim 15, wherein the histogram for the firstbiometric signal comprises a histogram of accumulated data for the firstbiometric signal obtained for a predetermined period of time, andwherein the predetermined condition comprises at least one of thehistogram for the first biometric signal or external information. 17.The method of claim 16, further comprising: receiving the externalinformation through a wireless communication circuit, wherein theexternal information comprises the demographic information.
 18. Themethod of claim 16, wherein the determining of the second value of thefirst biometric signal as the reference value comprises: determiningthat the second value of the first biometric signal is included within aspecific range of at least one of the histogram or the externalinformation; and based on determining that the second value of the firstbiometric signal is included within the specific range, updating thereference value to be the second value of the first biometric signal.